Table of contents : Contents Chapter 1: Between Hype and Hope, on the Cutting Edge of Precision Cancer Medicine Chapter 2: Molecular Diagnostics in Cancer: A Fundamental Component of Precision Oncology 2.1 History of Molecular Diagnostics in Cancer 2.2 Clinical Applications of Molecular Diagnostics in Cancer Care 2.2.1 Taxonomy and Molecular Biomarkers for Prediction of Therapy, Diagnosis, and Prognosis 2.2.1.1 Predictive Biomarkers 2.2.1.2 Diagnostic Biomarkers 2.2.1.3 Prognostic Biomarkers 2.2.2 Disease Monitoring 2.2.3 Cancer Prevention and Early Detection 2.3 Frontiers in Molecular Diagnostics of Cancer 2.3.1 Current State-of-the-Art Nucleic-Acid-Based Analysis: Next-Generation Sequencing 2.3.2 Liquid Biopsy 2.3.3 Current Challenges and Near Term Solutions 2.3.4 Future Perspective References Chapter 3: Clinical Interpretation 3.1 Introduction 3.2 History 3.3 Current Developments 3.3.1 Acquisition 3.3.2 Analysis 3.3.3 Action 3.3.4 Case Study: PHIAL 3.4 Challenges 3.4.1 Tissue Acquisition 3.4.2 Sequencing Approaches and Infrastructure 3.4.3 Clinical Adoption 3.5 Future Approaches 3.5.1 Acquisition Improvements 3.5.2 Analysis Improvements 3.5.3 Action Improvements 3.6 Conclusion References Chapter 4: Precision Cancer Medicine and Clinical Trial Design 4.1 Introduction 4.2 Target Discovery and Validation 4.3 Implications of Tumor Heterogeneity 4.4 Clinical Trial Paradigm 4.5 Enrichment and Adaptive Strategies 4.6 Umbrella or Master Trials 4.7 Basket Trials 4.8 N of 1 Trial 4.9 Conclusion References Chapter 5: Resistance to Anti-Cancer Therapeutics 5.1 Introduction 5.2 Chemotherapy Resistance 5.2.1 Introduction 5.2.2 Modulation of Drug Efflux from Cells 5.2.3 Intratumoral Heterogeneity and Cancer Stem Cells 5.2.4 DNA Damage Checkpoint and Repair Mechanisms 5.2.5 Genomic Complexity and Acquisition of Specific Mutations 5.2.6 Specific Gene Alterations 5.2.7 Other Mechanisms of Chemotherapy Resistance 5.3 Resistance to Targeted Therapies 5.3.1 BCR-ABL Inhibitors 5.3.2 EGFR Inhibitors 5.3.3 BRAF-V600E Inhibitors 5.3.4 HER2 (ERBB2) Targeted Therapies 5.3.5 ALK Inhibitors 5.3.6 Proteasome Inhibitors 5.3.7 VEGF Inhibitors 5.3.8 BTK Inhibitors 5.4 Conclusions References Chapter 6: Exceptional Responders 6.1 Introduction 6.2 Initial Whole Genome Sequencing (WGS) of an Exceptional Responder in Urothelial Carcinoma 6.3 Exceptional Response to mTOR Inhibitor Therapy and Pathway Convergence in Clonal Heterogeneity 6.4 Concurrent mTOR Mutations and Sensitivity to mTOR Inhibition as a Component of Combination Therapy 6.5 Curative Response to Combination Therapy in the Context of a Hypomorphic RAD50 Mutation 6.6 Analysis of Exceptional Responses to Treatment with Immunotherapy 6.7 Analysis of Exceptional Responses to Treatment with Chemotherapy 6.8 Occult Biomarkers Identified by Outlier Analysis 6.9 Mechanisms of Acquired Resistance Following Initial Exceptional Response 6.10 NCI Exceptional Responders Initiative 6.11 Conclusions and Future Steps References Chapter 7: Immunogenomics 7.1 Introduction and History of Immunogenomics 7.2 Preclinical Models Demonstrate Relevance of Immunogenomics to Tumor Fate 7.3 Neoantigen Prediction 7.4 Technologies to Detect a Neoantigen-Specific T Cell Response 7.5 Evidence for T-Cell Reactivity to Neoantigens in Patients Treated with Checkpoint Blockade Immunotherapy 7.6 Unanswered Questions and Future Directions References Chapter 8: Managing Germline Findings from Molecular Testing in Precision Oncology 8.1 Overview of Molecular Testing in Oncology 8.2 Molecular Testing in Oncology Care – Background 8.2.1 Tumor Molecular Testing for Treatment Planning 8.3 Germline Molecular Testing for Hereditary Cancer Risk 8.4 Next Generation Sequencing Technologies – Impact on Clinical Molecular Testing 8.5 How Common Are Germline Findings in Patients with Cancer? 8.6 Integrating Tumor and Germline Testing 8.7 Patient Preference, Right “Not to Know” 8.8 Informed Consent 8.9 Genetic Service Delivery 8.10 Case Examples 8.10.1 PGVs Can Have Relevance for Cancer Treatment 8.10.2 PGVs May Have Been Previously Missed 8.10.3 PGVs May Not Have Been Expected 8.11 Summary References Chapter 9: Ethical, Legal, and Social Implications of Precision Cancer Medicine 9.1 Introduction 9.2 Precision Cancer Medicine and Distributive Justice 9.2.1 Resource Allocation 9.2.2 Health Disparities 9.3 Informed Consent and Patient Education 9.3.1 Further Considerations in Precision Cancer Studies 9.3.2 Issues in Health Communication 9.3.3 Consenting Pediatric Participants 9.4 Return of Sequencing Results 9.4.1 Disclosing Risks for Adult-Onset Conditions in Childhood 9.4.2 Disclosing Results of Deceased Patients 9.4.3 Disclosing Risks for Diseases Other than Cancer 9.4.4 Legal Issues for Clinicians and Researchers 9.5 Conclusions References Chapter 10: Liquid Biopsy: Translating Minimally Invasive Disease Profiling from the Lab to the Clinic 10.1 Introduction 10.2 Circulating Tumor Cells (CTCs) 10.3 CTC Enrichment 10.4 Clinical Applications of CTCs: Enumeration 10.5 Beyond Enumeration: CTC Characterization and Analysis 10.6 Cell Free DNA (cfDNA) 10.7 Clinical Applications of cfDNA 10.8 Cell Free RNA and MicroRNA 10.9 The Rapidly Evolving Cell-Free Landscape 10.10 Extracellular Vesicles (EVs) 10.11 EV Isolation 10.12 Clinical Applications of EVs 10.13 Conclusion References Chapter 11: Data Portals and Analysis 11.1 The Evolution of Cancer Genomics 11.2 Navigating the Maze of Omics Data: Challenges and Opportunities 11.3 Data Portals and Public Repositories 11.3.1 Progress and Observations from Public Projects 11.3.2 Public Repositories for Cancer Genomics Data 11.3.2.1 The Cancer Genome Atlas (TCGA) [6] 11.3.2.2 Therapeutically Applicable Research to Generate Effective Treatments (TARGET) [7] 11.3.2.3 Cancer Genome Characterization Initiative (CGCI) [8] 11.3.2.4 Cancer Cell Line Encyclopedia (CCLE) [9] 11.3.2.5 International Cancer Genome Consortium (ICGC) [10] 11.3.2.6 AACR Project GENIE (Genomics Evidence Neoplasia Information Exchange) [12] 11.3.2.7 Genomic Data Commons (GDC) Data Portal [13] 11.3.2.8 Database of Genotypes and Phenotypes (dbGaP) [16] 11.3.2.9 European Genome-phenome Archive (EGA) [18] 11.3.2.10 ArrayExpress [19] 11.3.2.11 Gene Expression Omnibus (GEO) [20] 11.3.2.12 Synapse [15] 11.3.2.13 GDAC Firehose (Genome Data Analysis Center) [17] 11.3.2.14 The cBioPortal for Cancer Genomics [14] 11.4 Data Analysis Platforms 11.4.1 Bridging the Gap for Translational Cancer Research 11.4.1.1 cBioPortal for Cancer Genomics [14] 11.4.1.2 Broad Institute Firebrowse [21] 11.4.1.3 COSMIC [22] 11.4.1.4 ICGC Data Portal [10] 11.4.1.5 UCSC Xena [23] 11.4.1.6 St. Jude PeCan Data Portal [24] 11.4.1.7 Brown MAGI [25] 11.5 Clinical Actionability Resource Integration References